How to Keep Digital Implementations on Track

By Andrew Hastert, Director, Digital Portfolio Strategy, Rockwell Automation

According to the latest Rockwell Automation Annual State of Smart Manufacturing Report, the global labor shortage and skills gap continues to be a top concern. It’s becoming increasingly challenging to attract, manage and retain skilled workers. But there is hope.

New and emerging technologies are filling skills gaps and amplifying effort, rather than replacing workers. This makes it possible for manufacturers to do more with less.

Increasing automation and introducing artificial intelligence (AI) and machine learning (ML) technologies are top strategies manufacturers are planning to optimize processes. But many people remain skeptical of the transformative promises of this technology and its ability to overcome workforce gaps.

Past implementation attempts may have resulted in endless pilot projects, where companies strive and fail to achieve the benefits of digital transformation, the Industrial Internet of Things (IIoT) or “big data casual AI.” In fact, this experience is so common, it’s coined its own buzzword — pilot purgatory.

Maybe you’ve personally suffered from pilot purgatory as you’ve been lured into the inflated expectations of the innovation of the moment, only to find the initial investment didn’t yield intended returns and required more investment at the end.

Riding the Wave

If you’ve attempted your own venture into applying technology in manufacturing and achieved mixed results, you’re not alone. A survey from McKinsey found more than 80% of companies were stuck in pilot mode for more than a year.

But adoption of new technologies over the last four years has been growing. According to the latest Rockwell Automation Annual State of Smart Manufacturing Report, 95% of manufacturing companies are using or evaluating smart manufacturing technology. There are good reasons for this growth, including:

• Continued inflation.
• Shortage of skilled workers mixed with a new generation of workers.
• The need to prove sustainability outcomes.
• The need to balance across many complex priorities.

Another reason we can’t overlook is the surprising boom of new generative AI (GenAI) capabilities along with the raw accessibility for even the smallest of companies. Raw adoption numbers speak for themselves. While it took Uber 70 months to achieve 100 million users, and Instagam only 30 months, ChatGPT set a new bar of just 2 months (see chart).

This adoption includes industrial plants, with more than 80% of manufacturers anticipating evaluating GenAI in their operations in 2024 and expecting their technology investments to increase 30% year on year. While the threat of pilot purgatory looms, company leaders clearly worry more about threats to the status quo amidst this time of rapid change.

Foreseeing the Future

Predictive maintenance is one use case for AI/ML with transformative possibilities, but many manufacturers are finding it difficult to achieve, taking a Big Data approach to a problem that requires context from the process and effort to engineer unique algorithms. And companies can’t afford to waste any more time in pilot purgatory or ignore the promise of predictive maintenance.

According to Reuters, manufacturing equipment in the United States is on average the oldest it’s been in over half a century. Maintenance of this equipment remains a critical indicator of downtime and, in turn, productivity. Yet, maintenance resources are dwindling.

Studies have shown that regular scheduled maintenance could be shutting down your operations more often and longer than planned. Because variable-frequency drives (VFDs) often run the most critical processes in your operations, it’s imperative they offer some type of predictive maintenance that monitors the health of the drive along with connected assets.

Detecting failures in time to schedule preventive maintenance and buy replacement parts saves countless hours and dollars. And given today’s supply chain and cost constraints, maximizing uptime has gone from a priority to a survival tactic.

Staying Ahead of the Curve

For example. by using intelligent VFDs already on your plant floor, along with predefined ML models from vendors with expertise in mechanical systems, you can now achieve predictive maintenance insights about your equipment without wiring new sensors, investing in cloud storage or hiring data scientists. Most manufacturers have no idea how smart their VFD can be, missing one of the most data-rich sources for their production.

There are other ways to get ahead:

• Choose partners you trust to understand your production and plant-wide technologies and bring innovative capacity to your projects.
• With a diverse team, identify the greatest opportunities for business outcomes in your operations.
• Develop your business case, success criteria and roadmap for scale.
• Work with a partner to stand up viable products focused on areas of greatest value.
• Recognize success in your immediate and extended teams.
• Share learnings, expand functionality, widen integrations and scale value across your operations.

Manufacturers’ biggest competitive weakness in the United States is a shrinking skilled workforce, and the top way leading companies are addressing the skills gap is by increasing automation and AI/ML. This technology presents a transformative opportunity to overcome these challenges and help improve productivity. It’s now possible to:

• Shorten the time to design, commission and operate new systems and equipment
• Focus limited maintenance resources on assets most likely to fail and equip teams with insights into the most probably cause of failure
• Perform root cause analyses in real-time (after eliminating outliers) without having to delve into heavy data engineering effort
• Save engineers time by helping them generate code using natural language prompts, automating routine tasks, and improving design efficiency
• Take otherwise hidden data and find insights to improve on quality, energy consumption and productivity
• Empower the next generation of talent to triage and fix plantwide issues with natural language interfaces

Don’t wait in fear of pilot purgatory. Lead your team to a place where you’re regularly delivering innovative outcomes using game-changing technologies. Tomorrow’s industry leaders — and today’s preferred employers — aren’t slowing down.

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